Adjunctive Atypical Antipsychotics in Major Depressive Disorder: What’s the Impact?

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JOURNAL CLUB

Major depressive disorder (MDD) is the leading cause of global disease burden as measured in both years lived with disability as well as disability adjusted life-years.¹ Aside from the human cost, there is significant economic burden incurred by sufferers as well as our health care system as a whole—a figure estimated to be $210.5 billion yearly.² Although half of this is accounted for by work-related absenteeism and reduced productivity losses, the other half is attributed to direct medical costs involved in management and treatment which is shared by patients, employees, and our society.

MDD can be difficult to treat to remission, as it is not uncommon for inadequate response to first-line treatment modalities. As such, MDD often requires alternative approaches—one of which is augmentation with second-generation antipsychotics (SGA). Several SGA augmentation options exist and 3 are currently FDA approved (aripiprazole, quetiapine extended release, and brexpiprazole), while others have substantial evidence based on literature (cariprazine, lurasidone^3-5). (Note that the olanzapine/fluoxetine combination is an entirely separate entity used for bipolar II; this article is only discussing augmentative agents). No clinical trial has compared the difference inefficacy of SGA augmentation, hence there is no guidance on which to use first.

In a value-based system where cost reduction is a major consideration, it is now more important than ever for physicians to optimize expenditure while preserving efficacy and outcomes. The authors of the study in this journal review⁶ evaluated the impact of SGA augmentation modalities on health care resource use and overall costs in real world practice. Unlike a previous similar observational study⁷, which compared adjunctive brexpiprazole with lurasidone and quetiapine in MDD and found no difference in such costs, this study has a longer follow-up time and greater sample size (uses more recent claims data from multiple large sources).

Structured investigation

Question. What is the impact of the choice of adjunctive SGA on overall medical costs and health care utilization for MDD?

Type of study. Retrospective cohort analysis of de-identified administrative claims data from several large nationally representative claims databases.

Population. The patients were gleaned from the following databases: MarketScan Commercial and Medicare Supplemental (inpatient, outpatient, and prescription drug claims of > 43.6 million employees, dependents, retirees in the United States with primary or Medicare supplemental coverage through privately insured fee for service, point of service, or capitated health plans); MarketScan Multi-State Medicaid (demographic and health care records of > 44 million Medicaid enrollees from multiple states); and Optum (claims and clinical data from various health care plans and providers for > 150 million). All were 18 years of age and older and identification was done based on the presence of at least 1 inpatient, or 2 outpatient claims for MDD based on ICD-9 and ICD-10 codes used between approximately 2014 and 2017. (See Table)

Patients were required to have had at least 1 prescription of aripiprazole, brexpiprazole, cariprazine, lurasidone and 150 mg to 300 mg augmentation dose range of quetiapine during this identification period with a mutually exclusive cohort for each medication. Participants were also required to be on an antidepressant during treatment for at least 30 days before augmentation. To ensure follow-up, data must have beenavailable for continued enrollment during treatment and 12 months following the index. Patientswith diagnoses of schizophrenia spectrum, bipolar disorder, Medicare/Medicaid dual eligible or capitated plans, were excluded.

Method. Baseline variables related to illness severity were examined in the 1-year pre-index period. Patient demographics included age, gender, insurance, Charlson Comorbidity Index (CCI), number of Healthcare Cost and Utilization project, chronic conditions (both psychiatric and medical), medication use, and emergency department (ED) and hospital visits.

Primary outcome measures were psychiatric hospitalization and cost (total inpatient and outpatient service costs, distinct from pharmacy costs) during the follow-up period of 1 year. Secondary outcomesincluded psychiatry pharmacy costs (sum of claims for psychiatric medications in oral or long-acting injectable from pharmacy or outpatient setting) and medication adherence (proportion of days covered calculated as the number of available days of index therapy divided by 365 with adherence considered as ≥80%).

Statistical analysis. Descriptive, unadjusted analyses were performed to assess differences among cohorts at baseline (χ2 tests for categorical variables, and 1-way analysis of variant Kruskal-Wallis test for continuous variables). To examine association among SGA augmentation and health outcomes, generalized linear models (GLM) with gamma distribution and log function were performed for psychiatric costs, given that the distribution of costs is right skewed.

A 2-part model was conducted for psychiatric hospitalization costs with logistic regression for psychiatric hospitalizations, and GLM for hospitalization costs among hospitalized patients. All models were adjusted for age, gender, insurance type, CCI, MDD with psychosis, psychiatric and medical comorbidities, ED visits, hospitalizations, non-index antipsychotic use, other psychiatric medications. In the absence of a single acceptable measure of MDD severity available in administrative claims data, ED and hospital utilization as well as non-index antipsychotic use were used as proxy for severity. Costs were adjusted to 2017 US dollars using medical care component of the consumer price index.

Results

Baseline characteristics. Almost 3 million patients with MDD were identified in the databases during the study period; of those patients, 1.8% started SGA augmentation during that time. After inclusion and exclusion criteria were applied, and cariprazine initiators were excluded because of the small sample size; 10,325 patients remained for the analysis (7657 aripiprazole, 1219 brexpiprazole, 827 lurasidone, and 622 quetiapine). Mean (SD) age was 48 (15.8), majority females (70.3%) and commercially insured (77%). Baseline characteristics differed among the adjunctive SGA cohorts—patients prescribed brexpiprazole were older but had lower ED visits and hospitalizations at baseline (p < 0.001 for all comparisons). Medication use at baseline was common and differed somewhat among the cohorts (p < 0.001 for all comparisons).

Analysis.Unadjusted psychiatric costs (excluding pharmacy costs) during the follow-up period were lowest for brexpiprazole with mean (SD) of $3371 (10,708) followed by aripriprazole with $3871 (13,937), lurasidone with $6224 (20,656), and quetiapine with $10,670 (37,689). Patients taking brexpiprazole had the lowest mean (SD) hospitalization costs [$763 (6317)]. While brexpiprazole had the highest psychiatric pharmacy costs [$8961 (6104)], lurasidone had the highest total psychiatric costs [$14,196 (21,541)].

After controlling for baseline differences, the adjusted psychiatric costs (excluding pharmacy costs) differed significantly across the cohorts (p < 0.001). Compared with brexpiprazole, the psychiatric costs were significantly higher with lurasidone ($1662; p < 0.001) and quetiapine ($3894; p < 0.001), but did not differ between aripiprazole and brexpiprazole ($91; p = 0.563). The adjusted psychiatric pharmacy costs were significantly higher in the brexpiprazole group compared to the others.

Among hospitalized patients, the adjusted psychiatric hospitalization costs were $15,159 (p < 0.001) higher in quetiapine than in brexpiprazole cohorts. The odds of psychiatric hospitalization were also significantly higher with quetiapine than brexpiprazole [2.11 (1.46–3.04); p < 0.001]. No statistically significant differences were observed in risk of hospitalization comparing aripiprazole and lurasidone with brexpiprazole cohorts (p > 0.05). Across the spectrum, the lowest psychiatric hospitalization rates were found with brexpiprazole (4.3%, p < 0.001) while the highest rate was with quetiapine (8.6%, p < 0.001).

Adherence was low overall (percent of proportion of days covered >= 0.8 = 26.8%) and differed among the cohorts; quetiapine had the highest unadjusted medication adherence (29.6%), and the lurasidone group had the lowest (20.7%).

The bottom line

Based on a manufacturer-sponsored retrospective review of insurance claims filed between 2014 and 2017, adjunctive use of the SGAs brexpiprazole or aripiprazole in patients with MDD was associated with lower psychiatric costs compared with lurasidone and quetiapine augmentation. In comparison to quetiapine, brexpiprazole also was associated with a lower risk of psychiatric hospitalization, with no significant difference found between lurasidone, aripiprazole, and brexpiprazole. With no existing SGA augmentation guidelines and no evidence of efficacy between the different agents, these data on health care costs and utilization may be a consideration to clinicians in their decision-making process.

Discussion

This large study based on the real world and with a 12-month follow up represents the latest and most comprehensive data regarding health care costs and utilization for patients with MDD who receive SGA augmentation. The authors believe the results are generalizable given the diverse sample of patients with a variety of insurance types. Earlier studies had limitations and did not compare brexpiprazole with aripiprazole. For example, a 2018 analysis conducted over a 6-month period found no differences in psychiatric costs between brexpiprazole, lurasidone, and quetiapine.⁶ Another analysis, based on clinical trial data with no head-to-head comparisons and follow-up found lower medical costs associated with brexpiprazole than quetiapine.⁷

There are several limitations:

• The authors point out that the MDD diagnosis was identified from health insurance claims, which are designed for reimbursement purposes and can contain errors. Also, the design required antidepressant treatment before SGA augmentation; however, this does not indicate whether the patient had an adequate antidepressant trial not the type and class of antidepressant. Additionally, information such as symptom relief and any type of measures to assess improvement of depressive symptoms could not be measured. The burden of disease among the different cohorts is hence not accounted for.

• Although the patients were indeed diverse, it is unclear how this can be generalizable to patients without insurance, who have very different profiles especially from a social determinants of health standpoint. The authors intentionally excluded anyone younger than 18, and the resultant sample inadvertently had an abundance of female participants around 48 years of age, predominantly with commercial insurance. There were also disproportionate numbers of patients on each of the SGA augmentation (74.2% were on aripiprazole, 11.8% on brexpiprazole, 8% on lurasidonel and 6% on quetiapine), which could skew the analysis and, as such, interpretations. This low sample size was the reason cariprazine was not included in the analysis as a cohort; hence, no data is available for this emerging modality. The Charleston comorbidity index, which quantifies an individual’s burden of disease and corresponding 1-year mortality risk, was 1 for all cohorts (the higher the score is toward 6, the higher the mortality risk and resource use).

• Interestingly, a low adherence rate was reported, in line with one of the bigger clinical challenges we face daily. Although adherence varied somewhat between the different agents, the difference was not overly significant. Given that this dropout rate was quite high, the data may be skewed to favor those adherent to treatment.

• Lastly, there seems to be heavy financial support from industry (the makers of brexpiprazole specifically), and the authors do report additional affiliations.

Although these data represent very useful information on a population-based level, a head to head prospectiverandomized-controlled trial evaluating the efficacy of the various SGA augmentative agents is still needed to substantiate the cost differences reported here.

Dr Stanciu is assistant professor of psychiatry at Dartmouth’s Geisel School of Medicine and Director of Addiction Services at New Hampshire Hospital, Concord, NH. He is Addiction Section Editor for Psychiatric Times®. Dr Gnanasegaram is assistant professor of psychiatry at Dartmouth’s Geisel School of Medicine and attending psychiatrist at New Hampshire Hospital, Concord, NH. The authors report no conflicts of interest concerning the subject matter of this article.

References

1. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. GBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Lancet. 2017;390(10100):1211-1259.

2. Greenberg PE, Fournier AA, Sisitsky T, Pike CT, Kessler RC. The economic burden of adults with major depressive disorder in the United States (2005 and 2010). J Clin Psychiatry. 2015;76(2):155-162.

3. Suppes T, Silva R, Cucchiaro J, et al. Lurasidone for the treatment of major depressive disorder with mixed features: a randomized, double-blind, placebo-controlled study. Am J Psychiatry. 2016;173(4):400–407.

4. Fava M, Durgam S, Earley W, et al. Efficacy of adjunctive low-dose cariprazine in major depressive disorder: a randomized, double-blind, placebo-controlled trial. Int Clin Psychopharmacol. 2018;33(6):312–321.

5. Durgam S, Earley W, Guo H, et al. Efficacy and safety of adjunctive cariprazine in inadequate responders to antidepressants: a randomized, double-blind, placebo-controlled study in adult patients with major depressive disorder. J Clin Psychiatry. 2016;77(03):371–378.

6. Yan T, Greene M, Chang E, et al. Impact of Atypical Antipsychotics as Adjunctive Therapy on Psychiatric Cost and Utilization in Patients with Major Depressive Disorder. Clinicoecon Outcomes Res. 2020;12:81-89.

7. Broder MS, Greene M, Yan T, Chang E, Hartry A, Yermilov I. Medication adherence, health care utilization, and costs in patients with major depressive disorder initiating adjunctive atypical antipsychotic treatment. Clin Ther. 2019;41:221–232.

8. Sussman M, Yu J, Kamat SA, et al. Cost-effectiveness of brexpiprazole adjunctive treatment for major depressive disorder. J Affect Disord. 2017;207:54–62.